Fullstack Data Analyst

Pleo
Copenhagen, Denmark, London, United Kingdom, Madrid, Spain, Lisbon, PortugalPosted 26 March 2026

Tech Stack

Job Description

Messy spend management is tricky business. And tedious processes are a lose-lose situation for all involved, not just finance. At Pleo, we're changing that. We build spend solutions that make managing money seamless, empowering, and surprisingly effective for finance teams and employees alike—with a vision to help all businesses ‘go beyond’. The word ‘Pleo’ actually means ‘more than you’d expect’, and living by that mantra has been the secret to our success over the last 10 years. Now, we’re at a pivotal moment in our journey; every move we make has a direct impact on our 40,000+ customers, our business, and our collective success. We need people who take pride in uncovering customer needs, who turn complex problems into simple solutions, challenge the way things are done (respectfully), and always aim high. With great ambitions driving us forward, we can’t say we’ve got this whole thing figured out. And frankly, that’s half the fun! What we can say is that we’re a driven, progressive, and, importantly, a kind bunch of 850+ people from over 100 nationalities, all committed to delivering the future of business spending, together. About the role We’re looking for a Full Stack Data Analyst to join our Critical Data Products (CDP) team at Pleo. In this role, you'll be a key player in turning payment data into actionable insights that drive decisions across the company. You'll work end-to-end — from building data models to creating dashboards and presenting recommendations to stakeholders. You’ll partner closely with Product and Engineering teams in the Payments area to help improve payment performance, reduce failures, and strengthen decision-making through high-quality metrics and insight tooling. You’ll also be part of the broader Product Hub, focused on enabling our full company to be data-driven, using analytics and AI to speed up. Please note applications will be open until Monday 30th March 2026 at 09.00 GMT. We will not review any applications before then so that everyone is given a fair chance, please take the time to submit your application. Who you’ll be working with You'll be reporting to the Manager of the CDP team which sits within the Product Hub in the Data department. The CDP team include members from Data Analytics, Data Engineering, Data Science and Analytics Engineering all working together to support a wide scope across KYC/Compliance, FinCrime, Credit, Card/Banking Infrastructure, Regulatory Reporting and product teams across Pleo, delivering critical data pipelines, dashboards, reporting, strategic insights and data enablement guidance. Our team values trust, reliability, business understanding, alignment, and proactivity. We build strong relationships with our stakeholders, provide reliable data products, stay on top of strategic priorities, and proactively bring insights that drive impact. What you’ll be doing As a Fullstack Data Analyst you will: Conduct analysis on transactional data, present insights, and share your recommendations with stakeholders. Support with payment migrations, incident follow-ups, and strategic work with clear, data-backed narratives, and work with engineers to ensure that the metadata passed is useful for downstream reporting. Empower internal teams with high-quality, self-serve reporting through dashboards and reports in Looker. Define and operationalise core payments metrics (for example success rate, approval/decline rates, processing costs, volume, and operational impact) by setting up robust analytics foundations in dbt. Support in automation of regulatory and compliance reports. What you bring Advanced SQL skills and solid experience with data modeling in dbt. Solid experience with data visualisation tools, specifically Looker and LookML. Hands-on experience in payments analytics and a solid grasp of core payment concepts (e.g., authorization/clearing/settlement, payment methods, decline reasons, chargebacks, fraud signals, risk). A strong sense of owne ... (truncated, view full listing at source)
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